# Function Differences with torchvision.transforms.RandomSolarize [](https://gitee.com/mindspore/docs/blob/r2.0/docs/mindspore/source_en/note/api_mapping/pytorch_diff/RandomSolarize.md) ## torchvision.transforms.RandomSolarize ```python class torchvision.transforms.RandomSolarize( threshold, p=0.5 ) ``` For more information, see [torchvision.transforms.RandomSolarize](https://pytorch.org/vision/0.10/transforms.html#torchvision.transforms.RandomSolarize). ## mindspore.dataset.vision.RandomSolarize ```python class mindspore.dataset.vision.RandomSolarize( threshold=(0, 255) ) ``` For more information, see [mindspore.dataset.vision.RandomSolarize](https://mindspore.cn/docs/en/r2.0/api_python/dataset_vision/mindspore.dataset.vision.RandomSolarize.html#mindspore.dataset.vision.RandomSolarize). ## Differences PyTorch: Randomly expose the image with a given probability by inverting all pixel values above the threshold. MindSpore: Select a random subrange from the specified threshold range and adjust the image pixel values within the subrange. ## Code Example ```python from PIL import Image from pathlib import Path import numpy as np import matplotlib.pyplot as plt import torchvision.transforms as T import mindspore.dataset.vision as vision orig_img = Image.open(Path('.') / 'test.jpg') def show_diff_image(image_original, image_transformed): num = 2 plt.subplot(1, num, 1) plt.imshow(image_original) plt.title("Original image") plt.subplot(1, num, 2) plt.imshow(image_transformed) plt.title("Random Solaried image") plt.show() # In MindSpore, randomly selects a subrange within the specified threshold range and sets the pixel value within the subrange to (255 - pixel). solarizer = vision.RandomSolarize(threshold=(10,100)) rand_sola_img = solarizer(orig_img) show_diff_image(orig_img, rand_sola_img) # Out: # Original image and Solarized image are showed with matplotlib tools # In torch, the RandomSolarize transform randomly solarizes the image by inverting all pixel values above the threshold. solarizer = T.RandomSolarize(threshold=192.0) solarized_imgs = solarizer(orig_img) show_diff_image(orig_img, solarized_imgs) # Out: # Original image and Solarized image are showed with matplotlib tools ```